Search Results (1,145)

Long-range underwater gliders (LRUGs) have emerged as essential platforms for sustained and autonomous observation in deep and remote marine environments. This paper provides a comprehensive review of their developmental status, performance characteristics, and application progress. Emphasis is placed on two critical enabling technologies that fundamentally determine endurance: lightweight, pressure-resistant hull structures and high-efficiency buoyancy-driven propulsion systems. First, the role of carbon fiber composite pressure hulls in enhancing energy capacity and structural integrity is examined, with attention to material selection, fabrication methods, compressibility compatibility, and antifouling resistance. Second, the evolution of buoyancy control systems is analyzed, covering the transition to hybrid active–passive architectures, rapid-response actuators based on smart materials, thermohaline energy harvesting, and energy recovery mechanisms. Based on this analysis, the paper identifies four key technical challenges and proposes strategic research directions, including the development of ultralight, high-strength structural materials; integrated multi-mechanism antifouling technologies; energy-optimized coordinated buoyancy systems; and thermally adaptive glider platforms. Achieving a system architecture with ultra-long endurance, enhanced energy efficiency, and robust environmental adaptability is anticipated to be a foundational enabler for future long-duration missions and globally distributed underwater glider networks. Full article

Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and harm marine ecosystems. This ocean energy can be harnessed through hybrid nanogenerators that combine triboelectric nanogenerators, electromagnetic generators, piezoelectric nanogenerators, and pyroelectric generators. These nanogenerators have advantages such as high-power density, robust design, easy operating principle, and cost-effective fabrication. However, the performance of these nanogenerators can be affected by the wear of their main components, reduction of wave frequency and amplitude, extreme corrosion, and sea storms. To address these challenges, future research on hybrid nanogenerators must improve their mechanical strength, including materials and packages with anti-corrosion coatings. Herein, we present recent advances in the performance of different hybrid nanogenerators to harvest ocean energy, including various transduction mechanisms. Furthermore, this review reports potential applications of hybrid nanogenerators to power devices in marine infrastructure or serve as self-powered MIoT monitoring sensor networks. This review discusses key challenges that must be addressed to achieve the commercial success of these nanogenerators, regarding design strategies with advanced simulation models or digital twins. Also, these strategies must incorporate new materials that improve the performance, reliability, and integration of future nanogenerator array systems. Thus, optimized hybrid nanogenerators can represent a promising technology for ocean energy harvesting with application in the maritime industry. Full article

In this study, we aimed to address the lack of systematic research on key collision dynamics parameters (elastic restitution coefficient) in the full mechanization of rapeseed operations, which hinders the development of precision agriculture. In this present work, the restitution coefficient of rapeseed was systematically investigated, and a predictive model (R² = 0.959) was also established by using Box–Behnken design response surface methodology (BBD-RSM). The results show that the collision restitution coefficient varies in the range of 0.539–0.649, with the key influencing factors ranked as follows: moisture content (M_c) > material layer thickness (L) > drop height (H). The EDEM simulation methodology was adopted to validate the experimental results, and the results show that there is a minimal relative error (−1% < δ < 1%) between the measured and simulated rebound heights, indicating that the established model shows a reliable prediction performance. Moreover, by comprehensively analyzing stress, strain, and energy during the collision process between rapeseed and Q235 steel, it can be concluded that the process can be divided into five stages—free fall, collision compression, collision recovery, rebound oscillation, and rebound stabilization. The maximum stress (1.19 × 10⁻² MPa) and strain (6.43 × 10⁻⁶ mm) were observed at the beginning of the collision recovery stage, which can provide some theoretical and practical basis for optimizing and designing rapeseed machines, thus achieving the goals of precise control, harvest loss reduction, and increased yields. Full article

Complex mechanical systems, such as agricultural combine harvesters, are subjected to dynamic excitations from multiple coupled sources, compromising structural integrity and operational reliability. Disentangling these vibrations to identify dominant sources and quantify their transmission paths remains a significant engineering challenge. This study proposes a robust diagnostic framework to address this issue. We employed a multi-condition vibration test with sequential source activation and an improved Operational Transfer Path Analysis (OTPA) method. Applied to a harvester chassis, the results revealed that vibration energy is predominantly concentrated in the 0–200 Hz frequency band. Path contribution analysis quantified that the “cutting header → conveyor trough → hydraulic cylinder → chassis frame” path is the most critical contributor to vertical vibration, with a vibration acceleration level of 117.6 dB. Further analysis identified the engine (29.3 Hz) as the primary source for vertical vibration, while lateral vibration was mainly attributed to a coupled resonance between the threshing cylinder (58 Hz) and the engine’s second-order harmonic. This study’s theoretical contribution lies in validating a powerful methodology for vibration source apportionment in complex systems. Practically, the findings provide direct, actionable insights for targeted structural optimization and vibration suppression. Full article

This Review examines up-to-date advancements in the integration of biomolecules and solar energy technologies, with a particular focus on biohybrid photovoltaic systems. Biomolecules have recently garnered increasing interest as functional components in a wide range of solar cell architectures, since they offer a huge variety of structural, optical, and electronic properties, useful to fulfill multiple roles within photovoltaic devices. These roles span from acting as light-harvesting sensitizers and charge transport mediators to serving as micro- and nanoscale structural scaffolds, rheological modifiers, and interfacial stabilizers. In this Review, a comprehensive overview of the state of the art about the integration of biomolecules across the various generations of photovoltaics is provided. The functional roles of pigments, DNA, proteins, and polysaccharides are critically reported improvements and limits associated with the use of biological molecules in optoelectronics. The molecular mechanisms underlying the interaction between biomolecules and semiconductors are also discussed as essential for a functional integration of biomolecules in solar cells. Finally, this Review shows the current state of the art, and the most significant results achieved in the use of biomolecules in solar cells, with the main scope of outlining some guidelines for future further developments in the field of biohybrid photovoltaics. Full article

Ecosystem services—the benefits humans derive from nature—are foundational to environmental sustainability and economic well-being, with carbon sequestration and storage standing out as critical regulating services in the fight against climate change. This study presents a comprehensive financial valuation of the carbon sequestration, storage and product substitution ecosystem services provided by the Hungarian forest-based sector. Using a multi-scenario framework, four complementary valuation concepts are assessed: total carbon storage (biomass, soil, and harvested wood products), annual net sequestration, emissions avoided through material and energy substitution, and marketable carbon value under voluntary carbon market (VCM) and EU Carbon Removal Certification Framework (CRCF) mechanisms. Data sources include the National Forestry Database, the Hungarian Greenhouse Gas Inventory, and national estimates on substitution effects and soil carbon stocks. The total carbon stock of Hungarian forests is estimated at 1289 million tons of CO₂ eq, corresponding to a theoretical climate liability value of over EUR 64 billion. Annual sequestration is valued at approximately 380 million EUR/year, while avoided emissions contribute an additional 453 million EUR/year in mitigation benefits. A comparative analysis of two mutually exclusive crediting strategies—improved forest management projects (IFMs) avoiding final harvesting versus long-term carbon storage through the use of harvested wood products—reveals that intensified harvesting for durable wood use offers higher revenue potential (up to 90 million EUR/year) than non-harvesting IFM scenarios. These findings highlight the dual role of forests as both carbon sinks and sources of climate-smart materials and call for policy frameworks that integrate substitution benefits and long-term storage opportunities in support of effective climate and bioeconomy strategies. Full article

Liquid crystal elastomers (LCEs) have shown great potential in the field of soft robotics due to their unique actuation capabilities. Despite the growing number of experimental studies in the soft robotics field, theoretical research remains limited. In this paper, a dynamic model of a bionic arm using an LCE fiber as artificial muscle is established, which exhibits periodic oscillation controlled by periodic illumination. Based on the assumption of linear damping and angular momentum theorem, the dynamics equation of the model oscillation is derived. Then, based on the assumption of linear elasticity model, the periodic spring force of the fiber is given. Subsequently, the evolution equations for the cis number fraction within the fiber are developed, and consequently, the analytical solution for the light-excited strain is derived. Following that, the dynamics equation is numerically solved, and the mechanism of the controllable oscillation is elucidated. Numerical calculations show that the stable oscillation period of the bionic arm depends on the illumination period. When the illumination period aligns with the natural period of the bionic arm, the resonance is formed and the amplitude is the largest. Additionally, the effects of various parameters on forced oscillation are analyzed. The results of numerical studies on the bionic arm can provide theoretical support for the design of micro-machines, bionic devices, soft robots, biomedical devices, and energy harvesters. Full article

Energy harvesting systems (EHSs) are widely used to power wireless sensors. Piezoelectric harvesters have the advantage of producing an electric signal directly related to the exciting force and can thus be used to power condition monitoring sensors in dynamically loaded structures such as bridges. The need for such monitoring is exemplified by the fact that the condition of close to 25% of public roadway bridges in, e.g., Germany is not satisfactory. Stack-based piezoelectric energy harvesting systems (pEHSs) installed near bridge bearings could provide information about the traffic and dynamic loads on the one hand and condition-dependent changes in the bridge characteristics on the other. This paper presents an approach to co-optimizing the design of the mechanical and electrical components using a nonlinear solver. Such an approach has not been described in the open literature to the best of the authors’ knowledge. The mechanical excitation is estimated through a finite element simulation, and the electric circuitry is modeled in Simulink to account for the nonlinear characteristics of rectifying diodes. We use real traffic data to create statistical randomized scenarios for the optimization and statistical variation. A main result of this work is that it reveals the strong dependence of the energy output on the interaction between bridge, harvester, and traffic details. A second result is that the methodology yields design criteria for the harvester such that the energy output is maximized. Through the case study of an actual middle-sized bridge in Germany, we demonstrate the feasibility of harvesting a time-averaged power of several milliwatts throughout the day. Comparing the total amount of harvested energy for 1000 randomized traffic scenarios, we demonstrate the suitability of pEHS to power wireless sensor nodes. In addition, we show the potential sensory usability for traffic observation (vehicle frequency, vehicle weight, axle load, etc.). Full article

In this paper, we presents a case study involving the implementation experience and a methodological framework through a comprehensive comparative analysis of the YOLOX and YOLOv12 object detection models for agricultural automation systems deployed in the Jetson AGX Orin edge computing platform. We examined the architectural differences between the models and their impact on detection capabilities in data-imbalanced potato-harvesting environments. Both models were trained on identical datasets with images capturing potatoes, soil clods, and stones, and their performances were evaluated through 30 independent trials under controlled conditions. Statistical analysis confirmed that YOLOX achieved a significantly higher throughput (107 vs. 45 FPS, p < 0.01) and superior energy efficiency (0.58 vs. 0.75 J/frame) than YOLOv12, meeting real-time processing requirements for agricultural automation. Although both models achieved an equivalent overall detection accuracy (F1-score, 0.97), YOLOv12 demonstrated specialized capabilities for challenging classes, achieving 42% higher recall for underrepresented soil clod objects (0.725 vs. 0.512, p < 0.01) and superior precision for small objects (0–3000 pixels). Architectural analysis identified a YOLOv12 residual efficient layer aggregation network backbone and area attention mechanism as key enablers of balanced precision–recall characteristics, which were particularly valuable for addressing agricultural data imbalance. However, NVIDIA Nsight profiling revealed implementation inefficiencies in the YOLOv12 multiprocess architecture, which prevented the theoretical advantages from being fully realized in edge computing environments. These findings provide empirically grounded guidelines for model selection in agricultural automation systems, highlighting the critical interplay between architectural design, implementation efficiency, and application-specific requirements. Full article

Microalgae proteins are increasingly recognized in the food and nutraceutical industries for their functional versatility and high nutritional value. Mild alkaline treatment is commonly used for cell wall degradation and intracellular protein solubilization, consequently enhancing the protein extraction yield. The findings of this study reveal that alkaline treatment alone, even at higher NaOH concentration (up to 0.3 M) and treatment time (up to 90 min), was ineffective (max. 2.4% yield) for the extraction of protein from Auxenochlorella protothecoides biomass. This challenge was significantly reduced through synergistic application of mechanical cell disruption using high-pressure homogenization (HPH) and alkaline solubilization. Single-pass HPH (35 k psi) alone without alkaline treatment led to 52.3% protein solubilization from wet biomass directly harvested from culture broth, while it was only 18.5% for spray-dried biomass. The combined effect of HPH and alkaline (0.1 M NaOH) treatment significantly increased protein extraction yield to 68.0% for a spray-dried biomass loading of 50 g L⁻¹. Through replacing spray-dried biomass with wet biomass, the requirement of NaOH was reduced by 5-fold to 0.02 M to achieve a similar yield of 68.1%. The process integration of HPH with the mild alkaline solubilization and utilization of wet biomass from culture broth showed high potential for industrialization of microalgae protein extraction. This method achieves high extraction yield while reducing alkaline waste and eliminating the need for energy-consuming drying of biomass, thereby minimizing the environmental impact. Full article

In this research, a single composite-type stretchable triboelectric nanogenerator (TENG) is proposed for efficient energy harvesting and handwriting recognition. The composite TENGs were fabricated by blending dielectric barium titanate (BT) and conductive carbon nanotubes (CNTs) in varying amounts into a styrene–butadiene rubber matrix. The energy harvesting efficiency depends on the type and amount of fillers, as well as their dispersion within the matrix. Stearic acid modification of BT enables near-nanoscale filler distribution, resulting in high energy conversion efficiencies. The composite achieved power efficiency, power density, charge efficiency, and charge density values of 1.127 nW/N, 8.258 mW/m³, 0.146 nC/N, and 1.072 mC/m³, respectively, under only 2% cyclic compressive strain at 0.85 Hz. The material performs better at low stress–strain ranges, exhibiting higher charge efficiency. The generated charge in the TENG composite is well correlated with the compressive stress, which provides a minimum activation pressure of 0.144 kPa, making it suitable for low-pressure sensing applications. A flat composite with dimensions of 0.02 × 6 × 5 cm³ can produce a power density of 26.04 W/m³, a charge density of 0.205 mC/m³, and an output voltage of 10 V from a single hand pat. The rubber composite also demonstrates high accuracy in handwriting recognition across different individuals, with clear differences in sensitivity curves. Repeated attempts by the same person show minimal deviation (<5%) in writing time. Additionally, the presence of reinforcing fillers enhances mechanical strength and durability, making the composite suitable for long-term cyclic energy harvesting and wearable sensor applications. Full article

Polyaniline (PANI) based thermoelectric materials have attracted much attention in flexible energy harvesting devices due to their unique molecular structure, excellent chemical stability, and low cost. However, the intrinsic thermoelectric performance of intrinsic PANI makes it difficult to meet the needs of practical applications due to its low electronic transport properties. This review focuses on the preparation methods and key strategies for developing high-performance PANI-based thermoelectric materials. It aims to comprehensively update knowledge regarding synthesis methods, microstructures, thermoelectric properties, and underlying mechanisms. The overall goal is to provide timely insights to promote the development of high-performance PANI-based thermoelectric materials. Full article

The threshing drum, a core component in combine harvesters, experiences significant unbalanced vibrations during high-speed rotation, leading to severe mechanical wear, increased energy consumption, elevated noise levels, potential safety hazards, and higher maintenance costs. A primary challenge is that excessive interference signals often obscure the fundamental frequency characteristics of the vibration, hampering balancing effectiveness. This study introduces a signal conditioning model to suppress such interference and accurately extract the unbalanced quantities from the raw signal. Leveraging this extracted vibration force signal, an automatic optimization method for the balancing counterweights was developed, solving calculation issues inherent in traditional approaches. This formed the basis for an automatic balancing control strategy and an integrated system designed for online monitoring and real-time control. The system continuously adjusts the rotation angles, θ₁ and θ₂, of the balancing weight disks based on live signal characteristics, effectively reducing the drum’s imbalance under both internal and external excitation states. This enables a closed loop of online vibration testing, signal processing, and real-time balance control. Experimental trials demonstrated a significant 63.9% reduction in vibration amplitude, from 55.41 m/s² to 20.00 m/s². This research provides a vital theoretical reference for addressing structural instability in agricultural equipment. Full article

Lateritic soils in tropical regions feature cohesive textures and high specific resistance, driving up energy demands for tillage and harvesting machinery. However, current equipment designs lack discrete element models that account for soil moisture variations, and the microscopic effects of water content on lateritic soil deformation remain poorly understood. This study aims to calibrate and validate discrete element method (DEM) models of lateritic soil at varying moisture contents of 20.51%, 22.39%, 24.53%, 26.28%, and 28.04% by integrating the Hertz–Mindlin contact mechanics with bonding and JKR cohesion models. Key parameters in the simulations were calibrated through systematic experimentation. Using Plackett–Burman design, critical factors significantly affecting axial compressive force—including surface energy, normal bond stiffness, and tangential bond stiffness—were identified. Subsequently, Box–Behnken response surface methodology was employed to optimize these parameters by minimizing deviations between simulated and experimental maximum axial compressive forces under each moisture condition. The calibrated models demonstrated high fidelity, with average relative errors of 4.53%, 3.36%, 3.05%, 3.32%, and 7.60% for uniaxial compression simulations across the five moisture levels. Stress–strain analysis under axial loading revealed that at a given surface displacement, both fracture dimensions and stress transfer rates decreased progressively with increasing moisture content. These findings elucidate the moisture-dependent micromechanical behavior of lateritic soil and provide critical data support for DEM-based design optimization of soil-engaging agricultural implements in tropical environments. Full article

Quality and mechanical resilience are crucial for reducing losses in fruit production and for supporting food chains. Indeed, integrating empirical data with rheological models bridges gaps in fruit processing equipment design. Therefore, the objective of this research is to analyze the relationship between the mechanical and physical properties of seven economically important fruits—nectarine, kiwi, cherry, apple, peach, pear, and apricot—to assess their mechanical behavior and post-harvest quality. Standardized compression, creep, and puncture tests were conducted to establish mechanical parameters, such as rupture force, elasticity, and deformation energy. Physical characteristics including size, weight, density, and moisture content were also measured. The results indicated significant differences among the various categories of fruits; apples and pears were most suitable for mechanical harvesting and long storage periods, whereas cherries and apricots were least resistant and susceptible to injury. Correlations were high among the physical measurements, tissue firmness, and viscoelastic properties, thereby confirming structural properties’ contribution in influencing fruit quality and handling efficiency. The originality of this research is in its holistic examination of physical and mechanical properties under standardized testing conditions, thus offering an integrated framework for enhancing post-harvest operations. These findings offer practical insights for optimizing harvesting, packaging, transportation, and quality monitoring strategies based on fruit-specific mechanical profiles. Full article